{"total":120,"rows":[{"id":"2412.05563","title":"A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions","created":"2024-12-07","cited_by_count":121,"area":null},{"id":"2406.12334","title":"What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering","created":"2024-06-18","cited_by_count":90,"area":null},{"id":"2410.13284","title":"Learning to Route LLMs with Confidence Tokens","created":"2024-10-17","cited_by_count":67,"area":null},{"id":"2406.11675","title":"BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models","created":"2024-06-17","cited_by_count":50,"area":null},{"id":"2407.14507","title":"Internal Consistency and Self-Feedback in Large Language Models: A Survey","created":"2024-07-19","cited_by_count":50,"area":"lr"},{"id":"2412.12472","title":"Knowledge Boundary of Large Language Models: A Survey","created":"2024-12-17","cited_by_count":40,"area":null},{"id":"2603.12273","title":"Aligning Language Models from User Interactions","created":"2026-02-18","cited_by_count":28,"area":"alignment"},{"id":"2502.12964","title":"Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer","created":"2025-02-18","cited_by_count":27,"area":null},{"id":"2502.17026","title":"Understanding the Uncertainty of LLM Explanations: A Perspective Based on Reasoning Topology","created":"2025-02-24","cited_by_count":25,"area":"lr"},{"id":"2505.11737","title":"TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning","created":"2025-05-16","cited_by_count":24,"area":"lr"},{"id":"2407.07342","title":"Multilingual Blending: LLM Safety Alignment Evaluation with Language Mixture","created":"2024-07-10","cited_by_count":22,"area":"alignment"},{"id":"2407.09726","title":"On Mitigating Code LLM Hallucinations with API Documentation","created":"2024-07-13","cited_by_count":21,"area":null},{"id":"2506.09338","title":"Know What You Don't Know: Uncertainty Calibration of Process Reward Models","created":"2025-06-11","cited_by_count":21,"area":"lr"},{"id":"2504.00762","title":"Do We Truly Need So Many Samples? Multi-LLM Repeated Sampling Efficiently Scales Test-Time Compute","created":"2025-04-01","cited_by_count":20,"area":"lr"},{"id":"2411.02708","title":"Exploring Response Uncertainty in MLLMs: An Empirical Evaluation under Misleading Scenarios","created":"2024-11-05","cited_by_count":19,"area":"mllm"},{"id":"2412.15176","title":"Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure","created":"2024-12-19","cited_by_count":18,"area":"lr"},{"id":"2410.12788","title":"Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception","created":"2024-10-16","cited_by_count":17,"area":"rag"},{"id":"2406.05213","title":"On Subjective Uncertainty Quantification and Calibration in Natural Language Generation","created":"2024-06-07","cited_by_count":16,"area":null},{"id":"2410.10786","title":"On Information-Theoretic Measures of Predictive Uncertainty","created":"2024-10-14","cited_by_count":16,"area":null},{"id":"2505.24858","title":"MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs","created":"2025-05-30","cited_by_count":16,"area":null},{"id":"2410.02721","title":"Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization","created":"2024-10-03","cited_by_count":15,"area":"rag"},{"id":"2504.19774","title":"If Concept Bottlenecks are the Question, are Foundation Models the Answer?","created":"2025-04-28","cited_by_count":15,"area":null},{"id":"2407.06426","title":"DebUnc: Improving Large Language Model Agent Communication With Uncertainty Metrics","created":"2024-07-08","cited_by_count":14,"area":"agents"},{"id":"2509.25532","title":"Calibrating Verbalized Confidence with Self-Generated Distractors","created":"2025-09-29","cited_by_count":14,"area":"synth"},{"id":"2506.01538","title":"LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation","created":"2025-06-02","cited_by_count":13,"area":"agents"},{"id":"2412.04209","title":"CALMM-Drive: Confidence-Aware Autonomous Driving with Large Multimodal Model","created":"2024-12-05","cited_by_count":12,"area":"driving"},{"id":"2412.05723","title":"Training-Free Bayesianization for Low-Rank Adapters of Large Language Models","created":"2024-12-07","cited_by_count":12,"area":null},{"id":"2510.25506","title":"Reflections on the Reproducibility of Commercial LLM Performance in Empirical Software Engineering Studies","created":"2025-10-29","cited_by_count":12,"area":null},{"id":"2412.09572","title":"Rethinking LLM Uncertainty: A Multi-Agent Approach to Estimating Black-Box Model Uncertainty","created":"2024-12-12","cited_by_count":11,"area":"lr"},{"id":"2506.00780","title":"Do not Abstain! Identify and Solve the Uncertainty","created":"2025-06-01","cited_by_count":11,"area":null},{"id":"2510.12040","title":"Uncertainty Quantification for Hallucination Detection in Large Language Models: Foundations, Methodology, and Future Directions","created":"2025-10-14","cited_by_count":11,"area":null},{"id":"2604.17112","title":"Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification","created":"2026-04-18","cited_by_count":10,"area":"lr"},{"id":"2408.12249","title":"LLMs are not Zero-Shot Reasoners for Biomedical Information Extraction","created":"2024-08-22","cited_by_count":9,"area":"lr"},{"id":"2501.01558","title":"Predicting the Performance of Black-box LLMs through Follow-up Queries","created":"2025-01-02","cited_by_count":9,"area":null},{"id":"2505.17773","title":"C-LoRA: Contextual Low-Rank Adaptation for Uncertainty Estimation in Large Language Models","created":"2025-05-23","cited_by_count":9,"area":null},{"id":"2407.15748","title":"MoRSE: Bridging the Gap in Cybersecurity Expertise with Retrieval Augmented Generation","created":"2024-07-22","cited_by_count":8,"area":"rag"},{"id":"2503.00069","title":"Societal Alignment Frameworks Can Improve LLM Alignment","created":"2025-02-27","cited_by_count":8,"area":"alignment"},{"id":"2506.10060","title":"Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems","created":"2025-06-11","cited_by_count":8,"area":null},{"id":"2605.06908","title":"Same Signal, Opposite Meaning: Direction-Informed Adaptive Learning for LLM Agents","created":"2026-05-07","cited_by_count":8,"area":"lr"},{"id":"2410.02499","title":"Defining Knowledge: Bridging Epistemology and Large Language Models","created":"2024-10-03","cited_by_count":7,"area":null},{"id":"2510.02279","title":"Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation","created":"2025-10-02","cited_by_count":7,"area":null},{"id":"2510.02671","title":"Uncertainty as Feature Gaps: Epistemic Uncertainty Quantification of LLMs in Contextual Question-Answering","created":"2025-10-03","cited_by_count":7,"area":null},{"id":"2506.19399","title":"Automated Detection of Pre-training Text in Black-box LLMs","created":"2025-06-24","cited_by_count":6,"area":null},{"id":"2508.12040","title":"Mind the Generation Process: Fine-Grained Confidence Estimation During LLM Generation","created":"2025-08-16","cited_by_count":6,"area":null},{"id":"2510.02377","title":"Uncertainty-Aware Answer Selection for Improved Reasoning in Multi-LLM Systems","created":"2025-09-30","cited_by_count":6,"area":"lr"},{"id":"2510.24222","title":"HACK: Hallucinations Along Certainty and Knowledge Axes","created":"2025-10-28","cited_by_count":6,"area":null},{"id":"2604.02543","title":"Overconfidence and Calibration in Medical VQA: Empirical Findings and Hallucination-Aware Mitigation","created":"2026-04-02","cited_by_count":6,"area":"mllm"},{"id":"2504.03579","title":"Hallucination Detection on a Budget: Efficient Bayesian Estimation of Semantic Entropy","created":"2025-04-04","cited_by_count":5,"area":null},{"id":"2505.19145","title":"Do Large Language Models (Really) Need Statistical Foundations?","created":"2025-05-25","cited_by_count":5,"area":null},{"id":"2508.08139","title":"Can LLMs Detect Their Confabulations? Estimating Reliability in Uncertainty-Aware Language Models","created":"2025-08-11","cited_by_count":5,"area":"agents"},{"id":"2510.05987","title":"Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs","created":"2025-10-07","cited_by_count":5,"area":"lr"},{"id":"2511.17170","title":"Hallucinate Less by Thinking More: Aspect-Based Causal Abstention for Large Language Models","created":"2025-11-21","cited_by_count":5,"area":"lr"},{"id":"2503.01688","title":"When an LLM is apprehensive about its answers -- and when its uncertainty is justified","created":"2025-03-03","cited_by_count":4,"area":null},{"id":"2505.07309","title":"Uncertainty Profiles for LLMs: Uncertainty Source Decomposition and Adaptive Model-Metric Selection","created":"2025-05-12","cited_by_count":4,"area":null},{"id":"2509.17445","title":"Semantic Reformulation Entropy for Robust Hallucination Detection in QA Tasks","created":"2025-09-22","cited_by_count":4,"area":null},{"id":"2509.23088","title":"The Geometry of Creative Variability: How Credal Sets Expose Calibration Gaps in Language Models","created":"2025-09-27","cited_by_count":4,"area":null},{"id":"2606.32032","title":"Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs","created":"2026-06-30","cited_by_count":4,"area":"alignment"},{"id":"2406.14099","title":"Let Guidelines Guide You: A Prescriptive Guideline-Centered Data Annotation Methodology","created":"2024-06-20","cited_by_count":3,"area":null},{"id":"2408.12095","title":"uMedSum: A Unified Framework for Advancing Medical Abstractive Summarization","created":"2024-08-22","cited_by_count":3,"area":null},{"id":"2505.18575","title":"Response Uncertainty and Probe Modeling: Two Sides of the Same Coin in LLM Interpretability?","created":"2025-05-24","cited_by_count":3,"area":null},{"id":"2506.00694","title":"Measuring Faithfulness and Abstention: An Automated Pipeline for Evaluating LLM-Generated 3-ply Case-Based Legal Arguments","created":"2025-05-31","cited_by_count":3,"area":null},{"id":"2506.06240","title":"Bridging External and Parametric Knowledge: Mitigating Hallucination of LLMs with Shared-Private Semantic Synergy in Dual-Stream Knowledge","created":"2025-06-06","cited_by_count":3,"area":"rag"},{"id":"2506.11166","title":"Test-Time-Scaling for Zero-Shot Diagnosis with Visual-Language Reasoning","created":"2025-06-11","cited_by_count":3,"area":"lr"},{"id":"2506.11812","title":"On the Performance of LLMs for Real Estate Appraisal","created":"2025-06-13","cited_by_count":3,"area":null},{"id":"2506.14387","title":"SEAT: Sparse Entity-Aware Tuning for Knowledge Adaptation while Preserving Epistemic Abstention","created":"2025-06-17","cited_by_count":3,"area":null},{"id":"2510.08389","title":"Revisiting Hallucination Detection with Effective Rank-based Uncertainty","created":"2025-10-09","cited_by_count":3,"area":null},{"id":"2605.00742","title":"Position: agentic AI orchestration should be Bayes-consistent","created":"2026-05-01","cited_by_count":3,"area":"agents"},{"id":"2605.23414","title":"When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems","created":"2026-05-22","cited_by_count":3,"area":"agents"},{"id":"2408.05456","title":"Path-LLM: A Shortest-Path-based LLM Learning for Unified Graph Representation","created":"2024-08-10","cited_by_count":2,"area":null},{"id":"2411.09689","title":"Probing LLM Hallucination from Within: Perturbation-Driven Approach via Internal Knowledge","created":"2024-11-14","cited_by_count":2,"area":null},{"id":"2412.15683","title":"Variability Need Not Imply Error: The Case of Adequate but Semantically Distinct Responses","created":"2024-12-20","cited_by_count":2,"area":null},{"id":"2508.04915","title":"ConfAgents: A Conformal-Guided Multi-Agent Framework for Cost-Efficient Medical Diagnosis","created":"2025-08-06","cited_by_count":2,"area":null},{"id":"2509.04464","title":"Can Multiple Responses from an LLM Reveal the Sources of Its Uncertainty?","created":"2025-08-28","cited_by_count":2,"area":null},{"id":"2510.13103","title":"ESI: Epistemic Uncertainty Quantification via Semantic-preserving Intervention for Large Language Models","created":"2025-10-15","cited_by_count":2,"area":null},{"id":"2510.21310","title":"Efficient semantic uncertainty quantification in language models via diversity-steered sampling","created":"2025-10-24","cited_by_count":2,"area":null},{"id":"2512.20012","title":"Reliable LLM-Based Edge-Cloud-Expert Cascades for Telecom Knowledge Systems","created":"2025-12-23","cited_by_count":2,"area":null},{"id":"2601.21003","title":"Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models","created":"2026-01-28","cited_by_count":2,"area":null},{"id":"2605.01133","title":"When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems","created":"2026-05-01","cited_by_count":2,"area":"lr"},{"id":"2605.28778","title":"Can LLMs Use Linguistic Uncertainty Markers to Reliably Reflect Intrinsic Confidence?","created":"2026-05-27","cited_by_count":2,"area":null},{"id":"2606.17312","title":"Quantifying Consistency in LLM Logical Reasoning via Structural Uncertainty","created":"2026-06-15","cited_by_count":2,"area":"lr"},{"id":"2506.16724","title":"The Role of Model Confidence on Bias Effects in Measured Uncertainties for Vision-Language Models","created":"2025-06-20","cited_by_count":1,"area":"mllm"},{"id":"2508.16230","title":"FlexMUSE: Multimodal Unification and Semantics Enhancement Framework with Flexible interaction for Creative Writing","created":"2025-08-22","cited_by_count":1,"area":null},{"id":"2511.19166","title":"Epistemic Familiarity is Associated With Belief Stability in Large Language Models","created":"2025-11-24","cited_by_count":1,"area":null},{"id":"2512.04843","title":"From Symptoms to Systems: An Expert-Guided Approach to Understanding Risks of Generative AI for Eating Disorders","created":"2025-12-04","cited_by_count":1,"area":null},{"id":"2601.23094","title":"Safer Policy Compliance with Dynamic Epistemic Fallback","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2602.06031","title":"AP-OOD: Attention Pooling for Out-of-Distribution Detection","created":"2026-02-05","cited_by_count":1,"area":null},{"id":"2603.07528","title":"TableMind++: An Uncertainty-Aware Programmatic Agent for Tool-Augmented Table Reasoning","created":"2026-03-08","cited_by_count":1,"area":"lr"},{"id":"2606.01120","title":"Diagnosing LLM Arbitration Behavior over Pre-evidence Epistemic States in RAG-based Fact-Checking","created":"2026-05-31","cited_by_count":1,"area":null},{"id":"2606.12587","title":"Strategic Decision Support for AI Agents","created":"2026-06-10","cited_by_count":1,"area":null},{"id":"2607.11881","title":"Metacognition in LLMs: Foundations, Progress, and Opportunities","created":"2026-07-13","cited_by_count":1,"area":null},{"id":"2608.28018","title":"Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning","created":"2026-08-28","cited_by_count":1,"area":"lr"},{"id":"2408.10474","title":"LeCov: Multi-level Testing Criteria for Large Language Models","created":"2024-08-20","cited_by_count":0,"area":null},{"id":"2410.12001","title":"Impacts of Continued Legal Pre-Training and IFT on LLMs' Latent Representations of Human-Defined Legal Concepts","created":"2024-10-15","cited_by_count":0,"area":null},{"id":"2503.14833","title":"Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability","created":"2025-03-19","cited_by_count":0,"area":"diffusion"},{"id":"2503.23105","title":"Open-Vocabulary Semantic Segmentation with Uncertainty Alignment for Robotic Scene Understanding in Indoor Building Environments","created":"2025-03-29","cited_by_count":0,"area":null},{"id":"2505.04354","title":"Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows","created":"2025-05-07","cited_by_count":0,"area":"agents"},{"id":"2506.00072","title":"Evaluating Prompt Engineering Techniques for Accuracy and Confidence Elicitation in Medical LLMs","created":"2025-05-29","cited_by_count":0,"area":null},{"id":"2506.14567","title":"Controlling Context: Generative AI at Work in Integrated Circuit Design and Other High-Precision Domains","created":"2025-06-17","cited_by_count":0,"area":null},{"id":"2506.22486","title":"Hallucination Detection with Small Language Models","created":"2025-06-24","cited_by_count":0,"area":"rag"},{"id":"2509.20088","title":"Causal Understanding by LLMs: The Role of Uncertainty","created":"2025-09-24","cited_by_count":0,"area":null}],"next_cursor":"100"}